Method for generating network optimizing information

ABSTRACT

There is provided a method for generating network optimizing information including the steps of identifying system devices that are comprised in a network, collecting metrics from the identified system devices, including collecting at least one metric relating to the operation, status, capability, limitations, expandability, scalability, or performance of the system devices, assessing the collected metrics according to a predetermined assessment protocol, generating a roster of metrics of interest, such metrics of interest being a group of the collected metrics that meet a selection criteria and not including other collected metrics that do not meet the selection criteria, and presenting each of the metrics of interest in a format suitable for a network operator to corrective actions with regard to the identified non-compliant metrics or to capitalize on the identified optimization opportunities with respect to the network.

BACKGROUND OF THE INVENTION

U.S. Pat. No. 7,444,263 to White et al points out that the efficient,optimum operation of large, complex systems, such as web-basedenterprise systems, requires the monitoring, careful analysis andidentification of system metrics that reflect the performance of thesystem and the use of information regarding system metrics to identifyprobable root causes of performance problems in complex, distributed,multi-tier applications. According to White et al '263, such metrics,which in general relate to the operation of database systems andapplication servers, operating systems, physical hardware, networkperformance, and so on, all must be monitored across networks that mayinclude many computers, each executing numerous processes, so thatproblems can be detected and corrected when or preferably before theyarise.

White et al '263 further points out that several known system monitoringmethods have attempted to identify and monitor only the metrics andcombinations of metrics that are significant in representing theoperation of a system and in detecting any abnormalities therein.However, according to White et at '263, the complexity of modern systemsand the large number of possibly significant metrics and combinations ofmetrics lead to circumstances in which a monitoring system or operatormay miss monitoring at least some of the significant metrics orcombinations of metrics.

One possible solution, according to White et al '263, is to clearly andunambiguously identify and provide information pertaining to only thosemetrics or combinations of metrics that are of significance to orusefully represent and reflect the performance of the system, such asabnormalities in system operation. However, according to White et at'263, the clear and unambiguous identification and presentation ofmetrics and combinations of metrics accurately reflecting systemperformance or problems, in turn, involves a number of data collectionand processing operations, each of which involves unique and significantproblems that have seriously limited the capabilities of knownperformance monitoring systems and, as a consequence, the performance ofthe systems being monitored.

It is thus clear that there is a need to measure the metrics of anetwork system, and especially to measure those metrics that trulyindicate the performance of the network system. However, even the clearand unambiguous identification and presentation of system metrics thatreflect the performance of the network system does not fully put thenetwork system operator in a favorable position to resolve the rootcauses that cause “out-of-limits” system metrics. Moreover, merelypresenting clear and unambiguous identification and presentation ofsystem metrics does not assist a network system operator in evaluatingthe desirability of, and/or the need for, improvements or enhancementsto the existing network system, up to and including fully replacing theexisting network system with a more robust network system. Thus, theneed exists for a method for generating network optimizing information,whereupon this network optimizing information can provide a networkoperator with tools to remediate current problems with a network, suchas bottleneck and undercapacity issues, as well as tools to guide anexpansion and enhancement of the network. Additionally, the need existsfor a system and a device for implementing such a method.

SUMMARY OF THE INVENTION

One object of the present invention is to provide a method forgenerating network optimizing information, whereupon this networkoptimizing information can provide a network operator with tools toremediate current problems with a network, such as bottleneck andundercapacity issues, as well as tools to guide an expansion andenhancement of the network.

According to one aspect of the present invention, there is provided amethod for generating network optimizing information including the stepsof identifying system devices that are comprised in a network,collecting metrics from the identified system devices, includingcollecting at least one metric relating to the operation, status,capability, limitations, expandability, scalability, or performance ofthe system devices, assessing the collected metrics according to apredetermined assessment protocol, generating a roster of metrics ofinterest, such metrics of interest being a group of the collectedmetrics that meet a selection criteria and not including other collectedmetrics that do not meet the selection criteria, and presenting each ofthe metrics of interest in a format suitable for a network operator tocorrective actions with regard to the identified non-compliant metricsor to capitalize on the identified optimization opportunities withrespect to the network.

According to another aspect of the present invention, there is provideda system for performing a method for generating network optimizinginformation, wherein the method includes the steps of identifying systemdevices that are comprised in a network, collecting metrics from theidentified system devices, including collecting at least one metricrelating to the operation, status, capability, limitations,expandability, scalability, or performance of the system devices,assessing the collected metrics according to a predetermined assessmentprotocol, generating a roster of metrics of interest, such metrics ofinterest being a group of the collected metrics that meet a selectioncriteria and not including other collected metrics that do not meet theselection criteria, and presenting each of the metrics of interest in aformat suitable for a network operator to corrective actions with regardto the identified non-compliant metrics or to capitalize on theidentified optimization opportunities with respect to the network.

Also according to the present invention, the method for generatingnetwork optimizing information may include the step of presenting eachof the metrics of interest in a format that identifies the assistingresource as a vendor offering services in resolving identifiednon-compliant metrics or capitalizing on the identified optimizationopportunities. Moreover, wherein the step of presenting each of themetrics of interest in a format may optionally include presenting atleast one of the metrics of interest in a format that identifies avendor which has been selected to be presented in preference to othervendors. Still further, in connection with the vendor which has beenselected to be presented in preference to other vendors, the vendor maybe selected as a function of a step of evaluating a group of vendors anddetermining that the vendor is the most suitable vendor for offeringservices relating to the particular metric of interest. This step ofevaluating a group of vendors may optionally include considering whethera vendor has paid value for an opportunity to be among the group ofevaluated vendors.

According to a further feature of the one aspect of the presentinvention, the method further comprises the step of providinginformation concerning the presence or absence of commonality between aproperty or value of a metric of interest and the properties and valuesof a selected group of the same metric measured among other networkoperators. This step of providing information to concerning the presenceor absence of commonality can include assigning a peer groupclassification to a network to classify the network relative to othernetworks that have been evaluated by the method.

Other aspects, embodiments and advantages of the present invention willbecome apparent from the following detailed description which, taken inconjunction with the accompanying drawings, which illustrate theprinciples of the invention by way of example.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features and advantages of the presentinvention, as well as the invention itself, will be more fullyunderstood from the following description of various embodiments whenread together with the accompanying drawings, in which:

FIG. 1 is a schematic illustration of the method of the presentinvention;

FIG. 2 is a schematic illustration of an exemplary network about whichthe method of the present invention can provide highly useable, readilyreferenced network intervention and network growth guiding informationfor the network operator;

FIG. 3 is a schematic representation of a typical computer of a networkof the type about which the method of the present invention can providehighly useable, readily referenced network intervention and networkgrowth guiding information for the network operator;

FIG. 4 is a diagrammatic illustration of metric correlationrelationships; and

FIG. 5 is a schematic representation of further details of the dashboardplatform.

DETAILED DESCRIPTION OF THE INVENTION

Reference is had to FIG. 1, which is a schematic illustration of themethod of the present invention and to FIG. 2, which is a schematicillustration of an exemplary network about which the method of thepresent invention can provide highly useable, readily referenced networkintervention and network growth guiding information for the networkoperator. This method, hereinafter denominated as a method forgenerating network optimizing information, can provide a networkoperator with tools to remediate current problems with a network, suchas bottleneck and undercapacity issues, as well as tools to guide anexpansion and enhancement of the network.

The information generating method is configured for use with a networkand, as seen in FIG. 2, an exemplary network 220 is to be understood asrepresenting any information technology or “IP” arrangement operable tostore, manipulate, and present information to the network operator. Asseen in FIG. 2, the exemplary network 220 can comprise componentsenabling the network to operate as a local area network, a wide areanetwork such as the Internet, and/or a wireless network operable toreceive a wireless signal from a transmitter 222. The computerscomprised by the network 220 may include desktop computers 224, lap-topcomputers 226, hand-held computers 228 (including wireless devices suchas wireless personal digital assistants (PDA) or mobile phones), or anyother type of computational arrangement of hardware and/or software. Theseveral computers may be connected to the network 220 via a server 230.It should be noted that any other type of hardware or software may beincluded in the system and be considered a component thereof.

It can thus be understood that the “IT” arrangement exemplified by thenetwork 220 comprises one or more computers in the general sense. Inthis connection, reference is had to FIG. 3, which is a schematicrepresentation of a typical computer 600 and the computer 600 includes aprocessor 602, a main memory 604 and a static memory 606, whichcommunicate with each other via a bus 608. The computer 600 may furtherinclude a video display unit 610 (e.g., a liquid crystal display (LCD)or a cathode ray tube (CRT)). The computer 600 also includes analphanumeric input device 612 (e.g., a keyboard), a cursor controldevice 614 (e.g., a mouse), a disk drive unit 616, a signal generationdevice 618 (e.g., a speaker), and a network interface device 620. Thedisk drive unit 616 includes a machine-readable medium 624 on which isstored a set of instructions implemented as software 626. The software626 is also shown to reside, completely or at least partially, withinthe main memory 604 and/or within the processor 602. The software 626may further be transmitted or received via the network interface device620 and a signal generation device 628 is also provided. It is to beunderstood that any suitable embodiment of a computer may form a portionor the entirety of the network 220 in that a computer is to be regardedas a machine readable medium including any mechanism for storing ortransmitting information in a form readable by a machine. For example, amachine readable medium includes read-only memory (ROM); random accessmemory (RAM); magnetic disk storage media; optical storage media; flashmemory devices; or any other type of media suitable for storing ortransmitting information.

As illustrated in FIG. 1, the information generating method 100 iscomprised of a number of core steps that are operably interconnected toone another in a manner to produce a highly useable, readily referencedintervention and growth guide for the network operator. The order inwhich the steps of the information generating method 100 are describedherein is not intended to be limiting insofar as connoting a preferredor necessary order in which the steps must be executed but it is tounderstood that particular requirements such as, for example, the needfor particular data to be available, may necessitate that certain stepscannot be executed until other predetermined steps have already beenexecuted.

A device identification and discovery step 110 includes identifying theexistence of, and the identifying addresses of, system devices, which isintended to broadly encompass hardware and software elements ofcomputers and other forms of processing units, interconnecting networks,storage units, databases, and application servers. Data is thencollected, during a metrics collection step 112, from the identifiedsystem devices and the particular data targeted to be collected isreferred to as “metrics” and metrics can be generally understood asinformation relating to the operation, status, capability, limitations,expandability, scalability, and/or performance of the system devices.

The metrics gathered during the metrics collection step 112 are thensubjected to a “daylighting” step 114 via which the metrics are assessedin accordance with any suitable or preferred assessment protocol. Forexample, each of the gathered metrics may be assessed with regard to itscompliance or non-compliance with a predetermined “in-compliance” valuerange. Additionally, the upper and lower limits of the “in-compliance”value range can be dynamically—updated after each execution cycle of theinformation generating method 100 or these upper and lower limits can beheld static until updated at other predetermined milestones.

A compliance tracking and opportunity spotting step 116 is performed togenerate a roster of those metrics that were identified during thedaylighting step 114 as being of interest for the reason, for example,that the particular metric was assessed as falling outside of itsassociated predetermined “in-compliance” value range or for the reasonthat a particular metric reveals that there may be an opportunity tore-configure, add to, or otherwise further optimize the network. Theassessment of whether a given metric should be regarded as a metric ofinterest may involve, for example, generating a normalized scoring ofthe deviation of the given metric of interest from an “in-compliance”range of values and this normalized scoring of the deviation of eachmetric of interest from its current threshold bounds permits acomparison and correlation of metric deviations.

In what will customarily be the last-to-be performed step of the coresteps of the information generating method 100, an analyzed metricdisplay step 118 is performed. During this core step, each of themetrics of interest identified during the compliance tracking andopportunity spotting step 116 is presented in a format suitable for thenetwork operator to, at the least, have a listing of the identifiednon-compliant metrics and/or optimization opportunities and, preferably,have a “roadmap” for undertaking corrective actions with regard to theidentified non-compliant metrics and/or capitalize on the identifiedoptimization opportunities. It is to be understood that the term“display” is used in a broad sense and encompasses all forms ofcommunication in visual, aural, and tactile format and including bothhuman-and machine-interface variations.

Having now provided an overview of the information generating method100, reference is further had to FIG. 1 for a description of a system ofthe present invention that is operable to execute the core steps of theinformation generating method 100 (as well as any supplemental stepsthat may be comprised in the information generating method 100) in amanner that achieves the goal of producing a highly useable, readilyreferenced intervention and opportunity guide for the network operator.This system, which is herein designated as the Task and OpportunityProject Roadmap or “TOPPER” system 460, is embodied in a plurality ofselected hardware and software elements and, in this connection, mayinclude functional operating units permitted to access the network 220for the purpose of performing a cycle of the information generatingmethod 100 and such a functional operating unit could be in the form,for example, of an on-site appliance or a remotely operated appliance.

A description will now be provided of several platforms of the TOPPERsystem 460 and including a description of the configuration andoperation of these platforms in executing the core steps of theinformation generating method 100, it being understood that eachplatform of the TOPPER system 460 is configured from an appropriatearrangement of the hardware and software elements of the TOPPER system460. The TOPPER system 460 includes a location platform 462 thatexecutes the sub-steps of the device identification and discovery step110 of the information generating method 100, a harvesting platform 464that executes the sub-steps of the metrics collection step 112 of theinformation generating method 100, an evaluation platform 466 thatexecutes the sub-steps of the daylighting step 114 of the informationgenerating method 100, a reference base platform 468 that executes thesub-steps of the compliance tracking and opportunity spotting step 116of the information generating method 100, and a dashboard platform 470that executes the sub-steps of the analyzed metric display step 118 ofthe information generating method 100.

It is to be understood that each of the location platform 462, theharvesting platform 464, the evaluation platform 466, the reference baseplatform 468, and the dashboard platform 470 may be an independentlyconfigured and operated arrangement of the hardware and softwareelements of the TOPPER system 460, or may alternatively be locatedwithin another arrangement of the hardware and software elements of theTOPPER system 460 that itself is the location of another one of theplatforms of the TOPPER system 460.

The dashboard platform 470 of the TOPPER system 460 is configured tomaintain a metrics catalog 472 and to perform a metrics catalog updateloop 474. Also, the dashboard platform 470 of the TOPPER system 460 isconfigured to maintain a potential optimizer stockage 476 and to performa potential optimizer update loop 478. The dashboard platform 470 of theTOPPER system 460 performs a paired association function 480 via which ametric of interest (which has been determined to be an existing metricalready cataloged in the metrics catalog 472 or which has been added tothe metrics catalog 472 via the execution of a cycle of the metricscatalog update loop 474) and a potential optimizer stocked in thepotential optimizer stockage 476 are associated with one another. Inthis connection, the metric of interest can be an existing metricalready cataloged in the metrics catalog 472 or a metric that has beenadded to the metrics catalog 472 via the execution of a cycle of themetrics catalog update loop 474. Each paired metric of interest andpotential optimizer is communicated to the dashboard platform 470 whichthen displays the paired items to the network operator in a manner to bedescribed in more detail below.

In addition to displaying each paired metric of interest and potentialoptimizer, the dashboard platform 470 provides further information thatcan assist the network operator in better resolving a reportednon-compliance situation or in identifying opportunities for the networkoperator to enhance the network. In this regard, the dashboard platform470 may be configured to provide an intentionally ordered presentationof the respective group of paired metrics of interest and potentialoptimizers that are yielded at the end of a given complete cycle of theinformation generating method 100—that is, a presentation of informationto the network operator with selected clusters of the information beingcommunicated visually, aurally, etc. to the network operator beforeother clusters of the information are communicated. The intentionallyordered presentation of the paired metrics of interest and potentialoptimizers may be arranged, for example, so as to provide the networkoperator with a hierarchal listing of paired metrics of interest andpotential optimizers based upon a given criticality ranking of themetrics. As another example, the intentionally ordered presentation ofthe paired metrics of interest and potential optimizers may be soarranged, for example, so as to provide the network operator with ahierarchal listing of paired metrics of interest and potentialoptimizers based upon directing the network operator to preferredresources that can help resolve metrics issues or capitalize uponidentified opportunities. Further in this connection, the preferredresources can be comprised of vendors who have a particular capabilityor vendors who are given preference relative to other vendors based upona sponsorship criteria (i.e., “sponsored” vendors are given apreferential showing in the display provided by the dashboard platform470 as opposed to “non-sponsored” vendors).

Reference is now had to FIG. 4, which is a schematic representation ofone format displayed by the dashboard, wherein it can be seen that thedashboard 470 visually displays an intentionally ordered presentation ofone metric of interest and potential optimizers. The exemplary formatdisplayed by the dashboard 470 in FIG. 4 includes a “banner”-typelisting 484 comprising information about a “sponsored” vendor and this“banner”-type listing 484 is presented in a text and graphics format.The “banner”-type listing 484 is presented as the topmost one of avertical listing of vendors which offer services relating the respectivemetric of interest. For the purposes of illustration, it is assumed thatthe other vendors 486 listed below the “banner”-type listing 484 are“non-sponsored” vendors. Information about the other vendors 486 listedbelow the “banner”-type listing 484 are displayed in a text-only formator in another format selected to be less noticeable than the“banner”-type listing 484 comprising information about a “sponsored”vendor. Thus, by virtue of its listing on the vertical listing ofvendors and its more noticeable presentation in both text and graphics,as opposed to text alone, the “banner”—type listing 484 comprisinginformation about a “sponsored” vendor is given a preferential showingin the display provided by the dashboard platform 470 as opposed to the“non-sponsored” vendors 486. ° Banner-type listings may be comprisedsolely of graphic, graphics and text, or text only and may include, forexample, rich media (audio/video), promotions, or any feature thatincreases the value of listing to a vendor or a potential vendor willingto give value in return for a status as a “sponsored” vendor.

The dashboard platform 470 can additionally be configured to provideinformation to the network operator concerning the presence or absenceof commonality between a property or value of a metric of interest andthe properties and values of a selected group of the same metricmeasured among other network operators. This “metric neighborhood”comparator function conveniently provides the network operator with areference point to be factored in when considering, for example, thepriority to be ascribed to remediating a metric of interest or the pathsupon which to expand or re-adjust the capabilities of the network 220.The dashboard platform 470 can communicate the paired metrics ofinterest and potential optimizers, and the further information that canassist the network operator in better resolving a reportednon-compliance situation or in identifying opportunities for the networkoperator to enhance the network, via any suitable format such as, forexample, an interactive screen 482 accessible by the network operator.

Reference is now had to FIG. 5, which is a schematic representation offurther details of the dashboard platform. A dashboard platform 570 maybe configured to provide an intentionally ordered presentation of therespective group of paired metrics of interest and potential optimizersthat are yielded at the end of a given complete cycle of the informationgenerating method 100—that is, a presentation of information to thenetwork operator with selected clusters of the information beingcommunicated visually, aurally, etc. to the network operator beforeother clusters of the information are communicated. The intentionallyordered presentation of the paired metrics of interest and potentialoptimizers may be arranged, for example, so as to provide the networkoperator with a hierarchal listing of paired metrics of interest andpotential optimizers based upon a given criticality ranking of themetrics. As another example, the intentionally ordered presentation ofthe paired metrics of interest and potential optimizers may be soarranged, for example, so as to provide the network operator with ahierarchal listing of paired metrics of interest and potentialoptimizers based upon directing the network operator to preferredresources that can help resolve metrics issues or capitalize uponidentified opportunities. Further in this connection, the preferredresources can be comprised of vendors who have a particular capabilityor vendors who are given preference relative to other vendors based upona sponsorship criteria (i.e., “sponsored” vendors are given apreferential showing in the display provided by the dashboard platform570 as opposed to “non-sponsored” vendors). The metric/optimizer pairingfacility 572 receives a “pairing” request from the dashboard platform570. The metric/optimizer pairing facility 572 commands a filter sort574 to retrieve a single potential optimizer from a potential optimizerstockage 576 or to retrieve a plurality of potential optimizers from thepotential optimizer stockage 576. The metric/optimizer pairing facility572 generates a conditional set that comprises one or more of potentialoptimizers that fall comply in a meaningful way with the pairingrequest. Potential optimizers may be in the format of a textpresentation, a text and graphics presentation, and may be in the natureof a “banner” ad, and/or include audio files, video files, etc. Theconditional set is forwarded by the metric/optimizer pairing facility572 to a relevancy scoring facility 578 that determines a relevancyscore for each potential optimizer contained in the conditional set. Arelevancy score can be composed based upon, for example, the degree ofresponsiveness that the potential optimizer offers to resolve or respondto the metric of interest. The relevancy scoring facility 578 transmiteach potential optimizer of the conditional set to a revenue harvestfacility 580 which is operated to rank or order the received potentialoptimizer as a function of a predetermined ranking schematic. Forexample, the revenue harvest facility 580 may function to assign asuperior rank to a given potential optimizer in contrast to the rankthat the revenue harvest facility 580 assigns to a different potentialoptimizer, with this different ranking being made on the basis that thefirst noted potential optimizer will direct the user to a vendor thatdelivers services in a more reliable and/or affordable manner than thedifferent vendor associated with the second noted potential optimizer.Alternatively, the revenue harvest facility 580 may function to assign asuperior rank to a given potential optimizer in contrast to the rankthat the revenue harvest facility 580 assigns to a different potentialoptimizer, with this different ranking being made on the basis that thefirst noted potential optimizer will direct the user to a vendor thathas paid value to the operator of the dashboard platform 570 for aranking preference consideration while the different vendor associatedwith the second noted potential optimizer has not paid value to theoperator of the dashboard platform 570 for a ranking preferenceconsideration. As noted, the dashboard platform can additionally beconfigured to provide information to the network operator concerning thepresence or absence of commonality between a property or value of ametric of interest and the properties and values of a selected group ofthe same metric measured among other network operators and this “metricneighborhood” comparator function can be configured in a variety of waysto selectively change the respective “peer” group of networks that havebeen assessed by the method of the present invention and which share thecommonality of the presence or absence of a property or value of aparticular metric of interest. Thus, with continuing reference to FIG.5, the dashboard 570 includes a peer group assessor 582 operablyconnected to the metric/optimizer pairing facility 572 and operable toassess each metric of interest and make a determination as to which“peer” group to appropriately classify the metric of interest. The peergroup assessor 582 is coupled to a peer group selector device 584 whichpermits a user to selectively assign a given network having a respectivemetric of interest with a predetermined property or value to arelatively smaller “peer” group of networks having the same respectivemetric of interest with the predetermined property or value and havingother shared commonality. Alternatively, a user can selectively assignthis given network having the respective metric of interest with thepredetermined property or value to a relatively larger “peer” group thatcomprises not only the relatively small “peer” group of networks butcomprises, as well, other networks. For example, a user can operate thepeer group selector device 584 to selectively assign the given networkto a relatively smaller “peer” group of networks having the samerespective metric of interest with the predetermined property or valueand having the additional shared commonality of being networks operatedby entities in the same industry group or entities offerings products orservices to a similar category of customers. While an embodiment of theinvention has been described and illustrated herein, it is to bedistinctly understood that the invention is not limited thereto, but maybe otherwise variously embodied and practiced within the scope of thefollowing claims.

What is claimed is:
 1. A method for generating network optimizinginformation, the method comprising: identifying system devices that arecomprised in a network; collecting metrics from the identified systemdevices, including collecting at least one metric relating to theoperation, status, capability, limitations, expandability, scalability,or performance of the system devices; assessing the collected metricsaccording to a predetermined assessment protocol; generating a roster ofmetrics of interest, such metrics of interest being a group of thecollected metrics that meet a selection criteria and not including othercollected metrics that do not meet the selection criteria; andpresenting each of the metrics of interest in a format suitable for anetwork operator to corrective actions with regard to the identifiednon-compliant metrics or to capitalize on the identified optimizationopportunities with respect to the network.
 2. The method of claim1,wherein the step of presenting each of the metrics of interest in aformat includes presenting at least one of the metrics of interest in aformat in which a resource is identified for assisting in resolvingidentified non-compliant metrics or capitalizing on the identifiedoptimization opportunities.
 3. The method of claim 2, wherein the stepof presenting each of the metrics of interest in a format includespresenting at least one of the metrics of interest in a format thatidentifies the assisting resource as a vendor offering services inresolving identified non-compliant metrics or capitalizing on theidentified optimization opportunities.
 4. The method of claim 3, whereinthe step of presenting each of the metrics of interest in a formatincludes presenting at least one of the metrics of interest in a formatthat identifies a vendor which has been selected to be presented inpreference to other vendors.
 5. The method of claim 4, wherein thevendor which has been selected to be presented in preference to othervendors has been selected as a function of a step of evaluating a groupof vendors and determining that the vendor is the most suitable vendorfor offering services relating to the particular metric of interest. 6.The method of claim 5, wherein the step of evaluating a group of vendorsincludes considering whether a vendor has paid value for an opportunityto be among the group of evaluated vendors.
 7. The method of claim 1,wherein the method identifies system devices that are comprised in anetwork operated as a local area network, a wide area network such asthe Internet, or a wireless network operable to receive a wirelesssignal.
 8. The method of claim 1, wherein the step of presenting each ofthe metrics of interest in a format suitable for a network operator tocorrective actions with regard to the identified non-compliant metricsor to capitalize on the identified optimization opportunities withrespect to the network includes providing an intentionally orderedpresentation of metrics of interest each paired with a respectivepotential optimizer, with each potential optimizer being an entityoffering services in resolving identified non-compliant metrics orcapitalizing on the identified optimization opportunities.
 9. The methodof claim 8, wherein the step of presenting each of the metrics ofinterest in a format includes a format communicating a hierarchallisting of paired metrics of interest and potential optimizers basedupon a given criticality ranking of the metrics.
 10. The method of claim8, wherein the step of presenting each of the metrics of interest in aformat includes a format communicating a hierarchal listing of pairedmetrics of interest and potential optimizers based upon directing thenetwork operator to preferred resources that can help resolve metricsissues or capitalize upon identified opportunities.
 11. The method ofclaim 10, wherein the step of presenting each of the metrics of interestin a format includes a format communicating information about vendorswho are given preference relative to other vendors based upon asponsorship criteria.
 12. The method of claim 10, wherein the step ofpresenting each of the metrics of interest in a format includes a formatcommunicating information about sponsored vendors that arepreferentially communicated relative to non-sponsored vendors.
 13. Themethod of claim 1 and further comprising the step of providinginformation to concerning the presence or absence of commonality betweena property or value of a metric of interest and the properties andvalues of a selected group of the same metric measured among othernetwork operators.
 14. The method of claim 13, wherein the step ofproviding information concerning the presence or absence of commonalityincludes assigning a peer group classification to a network to classifythe network relative to other networks that have been evaluated by themethod.